An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measur...An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.展开更多
A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the chara...A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.展开更多
数字预失真(Digital Pre-Distortion,DPD)能够提高功率放大器的线性度,并减少非线性失真对信号传输的影响。针对大容量数据高带宽和低信噪比的环境,在系统呈现一定稀疏性时,传统最小均方(Least Mean Square,LMS)无法快速收敛识别功放逆...数字预失真(Digital Pre-Distortion,DPD)能够提高功率放大器的线性度,并减少非线性失真对信号传输的影响。针对大容量数据高带宽和低信噪比的环境,在系统呈现一定稀疏性时,传统最小均方(Least Mean Square,LMS)无法快速收敛识别功放逆模型。因此,提出一种改进的二范数约束的最小均方(Two Norm Constraint Least Mean Square,2-LMS)算法,通过改变代价函数表达式和步长表达函数来提高算法收敛速度,并减少收敛过程中的稳态误差。此外,引入相邻时刻误差的自相关矩阵,提高了预失真系统的抗噪能力。仿真实验结果表明,基于2-LMS算法的预失真系统在抗噪性能、收敛速度及带外抑制等方面明显优于传统自适应算法,且预失真的邻信道功率比(Adjacent Channel Power Ratio,ACPR)比原基于LMS算法预失真系统优化了-10.3 dB,矢量误差幅度(Error Vector Magnitude,EVM)指标优化了7.5%。展开更多
This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and position...This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.展开更多
复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性...复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。展开更多
There are great challenges for traditional three-dimensional( 3-D) interferometric inverse synthetic aperture radar( In ISAR) imaging algorithms of ship targets w ith 2-D sparsity in actual radar imaging system. To de...There are great challenges for traditional three-dimensional( 3-D) interferometric inverse synthetic aperture radar( In ISAR) imaging algorithms of ship targets w ith 2-D sparsity in actual radar imaging system. To deal w ith this problem,a novel 3-D In ISAR imaging method is proposed in this paper.First,the high-precision gradient adaptive algorithm w as adopted to reconstruct the echoes in range dimension. Then the method of minimizing the entropy of the average range profile w as applied to estimate the parameters w hich are used to compensate translation components of the received echoes. Besides,the phase adjustment and image coregistration of the sparse echoes w ere achieved at the same time through the approach of the joint phase autofocus. Finally,the 3-D geometry coordinates of the ship target w ith 2-D sparsity w ere reconstructed by combining the range measurement and interferometric processing of the ISAR images. Simulation experiments w ere carried out to verify the practicability and effectiveness of the algorithm in the case that the received echoes are in 2-D sparsity.展开更多
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class unifo...Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.展开更多
The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circ...The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.展开更多
One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is propo...One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is proposed. The 2-D nature of the algorithm provides it an advantage of circumventing the roundabout transforming procedures between two dimensional （2-D） image deta and one-dimensional （l-D） signal. Moreover the combination of the Newton （fixed-point algorithm） and natural gradient algorithms in this composite algorithm increases its efficiency and robustness. The convincing results of a successful example in functional magnetic resonance imaging （fMRI） show the potential application of composite 2-D ICA in the brain activity detection.展开更多
A 3-D numerical model for calculating flow in non-curvilinear coordinates was established in this article. The flow was simulated by solving the full Reynolds-averaged Navier-Stokes equations with the RNG κ-ε turbul...A 3-D numerical model for calculating flow in non-curvilinear coordinates was established in this article. The flow was simulated by solving the full Reynolds-averaged Navier-Stokes equations with the RNG κ-ε turbulence model. In the horizontal x-y-plane, a boundary-fitted curvilinear co-ordinate system was adopted, while in the vertical direction, a σ co-ordinate transformation was used to represent the free surface and bed topography. The water level was determined by solving the 2-D Poisson equation derived from 2-D depth averaged momentum equations. The finite-volume method was used to discretize the equations and the SIMPLEC algorithm was applied to acquire the coupling of velocity and pressure. This model was applied to simulate the meandering channels and natural rivers, and the water levels and the velocities for all sections were given. By contrasting and analyzing, the agreement with measurements is generally good. The feasibility studies of simulating flow of the natural fiver have been conducted to demonstrate its applicability to hydraulic engineering research.展开更多
文摘An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.
基金This project was supported by Science and Technology Research Emphasis Fund of Ministry of Education(204010) .
文摘A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.
文摘数字预失真(Digital Pre-Distortion,DPD)能够提高功率放大器的线性度,并减少非线性失真对信号传输的影响。针对大容量数据高带宽和低信噪比的环境,在系统呈现一定稀疏性时,传统最小均方(Least Mean Square,LMS)无法快速收敛识别功放逆模型。因此,提出一种改进的二范数约束的最小均方(Two Norm Constraint Least Mean Square,2-LMS)算法,通过改变代价函数表达式和步长表达函数来提高算法收敛速度,并减少收敛过程中的稳态误差。此外,引入相邻时刻误差的自相关矩阵,提高了预失真系统的抗噪能力。仿真实验结果表明,基于2-LMS算法的预失真系统在抗噪性能、收敛速度及带外抑制等方面明显优于传统自适应算法,且预失真的邻信道功率比(Adjacent Channel Power Ratio,ACPR)比原基于LMS算法预失真系统优化了-10.3 dB,矢量误差幅度(Error Vector Magnitude,EVM)指标优化了7.5%。
基金supported by Nanyang Technological University,Singapore under the Wallenberg-NTU Presidential Postdoctoral Fellowship and the Natural Science Foundation in Heilongjiang Province,China(YQ2022F003).
文摘This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.
文摘复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61622107 and 61871146)the Fundamental Research Funds for the Central Universities
文摘There are great challenges for traditional three-dimensional( 3-D) interferometric inverse synthetic aperture radar( In ISAR) imaging algorithms of ship targets w ith 2-D sparsity in actual radar imaging system. To deal w ith this problem,a novel 3-D In ISAR imaging method is proposed in this paper.First,the high-precision gradient adaptive algorithm w as adopted to reconstruct the echoes in range dimension. Then the method of minimizing the entropy of the average range profile w as applied to estimate the parameters w hich are used to compensate translation components of the received echoes. Besides,the phase adjustment and image coregistration of the sparse echoes w ere achieved at the same time through the approach of the joint phase autofocus. Finally,the 3-D geometry coordinates of the ship target w ith 2-D sparsity w ere reconstructed by combining the range measurement and interferometric processing of the ISAR images. Simulation experiments w ere carried out to verify the practicability and effectiveness of the algorithm in the case that the received echoes are in 2-D sparsity.
基金Supported by the CRSRI Open Research Program(CKWV2013225/KY)the Priority Academic Program Development of Jiangsu Higher Education Institution+2 种基金the Open Project Foundation of Key Laboratory of the Yellow River Sediment of Ministry of Water Resource(2014006)the State Key Lab of Urban Water Resource and Environment(HIT)(ES201409)the Open Project Program of State Key Laboratory of Food Science and Technology,Jiangnan University(SKLF-KF-201310)
文摘Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
基金Sponsored by The National Natural Science Foundation of China(60872065)Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation(20105152026)State Key Laboratory Open Fund of Novel Software Technology,Nanjing University(KFKT2010B17)
文摘The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.
基金Supported by the 973 Project (No.2003CB716106), NSFC (No.90208003, 30200059), TRAPOYT, Doctor Training Fund of MOE, PRC, Key Research Project of Science and Technology of MOE, Fok Ying Tong Education Foundation (No.91041)
文摘One important application of independent component analysis （ICA） is in image processing. A two dimensional （2-D） composite ICA algorithm framework for 2-D image independent component analysis （2-D ICA） is proposed. The 2-D nature of the algorithm provides it an advantage of circumventing the roundabout transforming procedures between two dimensional （2-D） image deta and one-dimensional （l-D） signal. Moreover the combination of the Newton （fixed-point algorithm） and natural gradient algorithms in this composite algorithm increases its efficiency and robustness. The convincing results of a successful example in functional magnetic resonance imaging （fMRI） show the potential application of composite 2-D ICA in the brain activity detection.
基金the National Basic Research Program of China (973 Program, Grant No. 2006CB403302)the National Natural Science Foundation of China (Grant No.50779006)the Natural Science Foundation of LiaoningProvince (Grant No. 20062170)
文摘A 3-D numerical model for calculating flow in non-curvilinear coordinates was established in this article. The flow was simulated by solving the full Reynolds-averaged Navier-Stokes equations with the RNG κ-ε turbulence model. In the horizontal x-y-plane, a boundary-fitted curvilinear co-ordinate system was adopted, while in the vertical direction, a σ co-ordinate transformation was used to represent the free surface and bed topography. The water level was determined by solving the 2-D Poisson equation derived from 2-D depth averaged momentum equations. The finite-volume method was used to discretize the equations and the SIMPLEC algorithm was applied to acquire the coupling of velocity and pressure. This model was applied to simulate the meandering channels and natural rivers, and the water levels and the velocities for all sections were given. By contrasting and analyzing, the agreement with measurements is generally good. The feasibility studies of simulating flow of the natural fiver have been conducted to demonstrate its applicability to hydraulic engineering research.
